{"id":"W2316126360","doi":"10.1021/jp4006422","title":"Large-Scale Quantitative Structure–Property Relationship (QSPR) Analysis of Methane Storage in Metal–Organic Frameworks","year":2013,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Metal-Organic Frameworks: Synthesis and Applications","field":"Chemistry","cited_by":237,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Quantitative structure–activity relationship; Methane; Multilinear map; Support vector machine; Metal-organic framework; Biological system; Decision tree; Nonlinear system; Linear regression; Computer science; Data mining; Chemistry; Mathematics; Adsorption; Machine learning; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005088995,0.0002375993,0.0007955462,0.00008005316,0.00006982352,0.00002863087,0.0006786785,0.0003014762,0.005178588],"category_scores_gemma":[0.0008290421,0.0001365676,0.0004302687,0.001214751,0.0001636009,0.0001758007,0.00009054003,0.00165306,0.0000148754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008421003,"about_ca_system_score_gemma":0.00007278645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003205425,"about_ca_topic_score_gemma":0.00001211496,"domain_scores_codex":[0.9981377,0.0001167643,0.0007768914,0.0002052579,0.0004912107,0.0002721791],"domain_scores_gemma":[0.9965858,0.001469458,0.0008794395,0.0006403025,0.0002911264,0.0001339125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002655202,0.0003400334,0.0006998266,0.00005997602,0.000738273,0.000001003216,0.001486484,0.001426582,0.9947376,0.0002446418,0.000086678,0.0001523674],"study_design_scores_gemma":[0.000389755,0.00002737568,0.005317281,0.0001216176,0.002258961,0.000007220035,0.003224783,0.01542395,0.9657915,0.007038696,0.0001332067,0.0002656342],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956041,0.0003165842,0.002519337,0.0004837392,0.00001515464,0.00007050138,0.00004766517,0.00001112372,0.00093181],"genre_scores_gemma":[0.9983408,0.00002008629,0.0009870488,0.00003426687,0.0001377274,0.000006874909,0.00001577367,0.00002785594,0.0004295097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02894607,"threshold_uncertainty_score":0.9957308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01648594554339814,"score_gpt":0.2665045046305115,"score_spread":0.2500185590871133,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}